Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study

Purpose The study investigates the efficacy of new features introduced to the selection process for medical school at the University of New South Wales, Australia: (1) considering the relative ranks rather than scores of the Undergraduate Medicine and Health Sciences Admission Test and Australian Te...

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Main Authors: Boaz Shulruf, Gary Mayer Velan, Sean Edward Kennedy
Format: Article
Language:English
Published: Korea Health Personnel Licensing Examination Institute 2022-11-01
Series:Journal of Educational Evaluation for Health Professions
Subjects:
Online Access:http://www.jeehp.org/upload/jeehp-19-31.pdf
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author Boaz Shulruf
Gary Mayer Velan
Sean Edward Kennedy
author_facet Boaz Shulruf
Gary Mayer Velan
Sean Edward Kennedy
author_sort Boaz Shulruf
collection DOAJ
description Purpose The study investigates the efficacy of new features introduced to the selection process for medical school at the University of New South Wales, Australia: (1) considering the relative ranks rather than scores of the Undergraduate Medicine and Health Sciences Admission Test and Australian Tertiary Admission Rank; (2) structured interview focusing on interpersonal interaction and concerns should the applicants become students; and (3) embracing interviewers’ diverse perspectives. Methods Data from 5 cohorts of students were analyzed, comparing outcomes of the second year in the medicine program of 4 cohorts of the old selection process and 1 of the new process. The main analysis comprised multiple linear regression models for predicting academic, clinical, and professional outcomes, by section tools and demographic variables. Results Selection interview marks from the new interview (512 applicants, 2 interviewers each) were analyzed for inter-rater reliability, which identified a high level of agreement (kappa=0.639). No such analysis was possible for the old interview since it required interviewers to reach a consensus. Multivariate linear regression models utilizing outcomes for 5 cohorts (N=905) revealed that the new selection process was much more effective in predicting academic and clinical achievement in the program (R2=9.4%–17.8% vs. R2=1.5%–8.4%). Conclusion The results suggest that the medical student selection process can be significantly enhanced by employing a non-compensatory selection algorithm; and using a structured interview focusing on interpersonal interaction and concerns should the applicants become students; as well as embracing interviewers’ diverse perspectives.
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spelling doaj.art-be14e99a8ca74a2ca2413eb19a8b56ec2023-07-05T04:44:27ZengKorea Health Personnel Licensing Examination InstituteJournal of Educational Evaluation for Health Professions1975-59372022-11-011910.3352/jeehp.2022.19.31457Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive studyBoaz ShulrufGary Mayer VelanSean Edward KennedyPurpose The study investigates the efficacy of new features introduced to the selection process for medical school at the University of New South Wales, Australia: (1) considering the relative ranks rather than scores of the Undergraduate Medicine and Health Sciences Admission Test and Australian Tertiary Admission Rank; (2) structured interview focusing on interpersonal interaction and concerns should the applicants become students; and (3) embracing interviewers’ diverse perspectives. Methods Data from 5 cohorts of students were analyzed, comparing outcomes of the second year in the medicine program of 4 cohorts of the old selection process and 1 of the new process. The main analysis comprised multiple linear regression models for predicting academic, clinical, and professional outcomes, by section tools and demographic variables. Results Selection interview marks from the new interview (512 applicants, 2 interviewers each) were analyzed for inter-rater reliability, which identified a high level of agreement (kappa=0.639). No such analysis was possible for the old interview since it required interviewers to reach a consensus. Multivariate linear regression models utilizing outcomes for 5 cohorts (N=905) revealed that the new selection process was much more effective in predicting academic and clinical achievement in the program (R2=9.4%–17.8% vs. R2=1.5%–8.4%). Conclusion The results suggest that the medical student selection process can be significantly enhanced by employing a non-compensatory selection algorithm; and using a structured interview focusing on interpersonal interaction and concerns should the applicants become students; as well as embracing interviewers’ diverse perspectives.http://www.jeehp.org/upload/jeehp-19-31.pdfalgorithmsconsensuslinear modelsmedical schoolsschool admission criteria
spellingShingle Boaz Shulruf
Gary Mayer Velan
Sean Edward Kennedy
Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study
Journal of Educational Evaluation for Health Professions
algorithms
consensus
linear models
medical schools
school admission criteria
title Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study
title_full Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study
title_fullStr Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study
title_full_unstemmed Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study
title_short Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study
title_sort medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in australia a descriptive study
topic algorithms
consensus
linear models
medical schools
school admission criteria
url http://www.jeehp.org/upload/jeehp-19-31.pdf
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